Job Description

Company Description ExaSynth builds AI-native execution infrastructure for autonomous scientific laboratories, connecting robotics, laboratory instruments, and scientific AI into a unified platform. The company focuses on enabling automated experimentation and closed-loop scientific discovery, helping research teams run more efficient and scalable lab operations. By orchestrating complex hardware and software systems, ExaSynth supports high-throughput, reproducible science across multiple domains. Team members collaborate at the intersection of robotics, real-time systems, and AI, contributing directly to next-generation scientific workflows.

Role Description The Principal Systems Architect (Distributed Robotics & Real-time OS) will lead the design and evolution of ExaSynth's core systems that coordinate distributed robots, lab instruments, and real-time control infrastructure. This full-time, hybrid role is based in Singapore, with a mix of on-site collaboration and work-from-home flexibility. Day-to-day responsibilities include defining system and software architecture for distributed robotics, specifying real-time operating system requirements, and ensuring robust integration between hardware controllers, orchestration services, and AI-driven decision engines. The role involves working closely with engineering teams to guide implementation, conduct design reviews, and establish best practices for reliability, scalability, and safety in autonomous lab environments. The Principal Systems Architect will also collaborate with product, operations, and scientific stakeholders to translate laboratory workflows into system requirements and oversee end-to-end system performance and resilience.

Qualifications

Strong System Architecture and Systems Design skills for complex, distributed, and real-time robotics platforms.
Hands-on Software Development experience in real-time or embedded systems, with a focus on reliable, maintainable code.
Proficiency in Systems Engineering, including requirements definition, trade-off analysis, and lifecycle management.
Demonstrated Integration skills across robotics, instrumentation, networks, and cloud or edge services.
Extensive experience with real-time operating systems (RTOS), distributed systems, and control frameworks for robotics or automation.
Background in autonomous systems, industrial automation, laboratory automation, or similar high-reliability environments.
Ability to lead cross-functional technical initiatives, mentor engineering teams, and communicate clearly with diverse stakeholders.
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field; equivalent practical experience considered.
Experience with AI-enabled control workflows, safety standards, and security for networked robotic systems is a strong plus.